在Amazon EC2上将HDFS与Apache Spark结合使用

Question

I have a spark cluster setup by using the spark EC2 script. I setup the cluster and I am now trying to put a file on HDFS, so that I can have my cluster do work.

On my master I have a file data.txt . I added it to hdfs by doing ephemeral-hdfs/bin/hadoop fs -put data.txt /data.txt

Now, in my code, I have:

JavaRDD<String> rdd = sc.textFile("hdfs://data.txt",8);

I get an exception when doing this:

Exception in thread "main" java.net.UnknownHostException: unknown host: data.txt
    at org.apache.hadoop.ipc.Client$Connection.<init>(Client.java:214)
    at org.apache.hadoop.ipc.Client.getConnection(Client.java:1196)
    at org.apache.hadoop.ipc.Client.call(Client.java:1050)
    at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:225)
    at com.sun.proxy.$Proxy6.getProtocolVersion(Unknown Source)
    at org.apache.hadoop.ipc.RPC.getProxy(RPC.java:396)
    at org.apache.hadoop.ipc.RPC.getProxy(RPC.java:379)
    at org.apache.hadoop.hdfs.DFSClient.createRPCNamenode(DFSClient.java:119)
    at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:238)
    at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:203)
    at org.apache.hadoop.hdfs.DistributedFileSystem.initialize(DistributedFileSystem.java:89)
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:1386)
    at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:66)
    at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:1404)
    at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:254)
    at org.apache.hadoop.fs.Path.getFileSystem(Path.java:187)
    at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:176)
    at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:208)
    at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:203)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.RangePartitioner.<init>(Partitioner.scala:123)
    at org.apache.spark.rdd.OrderedRDDFunctions.sortByKey(OrderedRDDFunctions.scala:62)
    at org.apache.spark.rdd.RDD.sortBy(RDD.scala:488)
    at org.apache.spark.api.java.JavaRDD.sortBy(JavaRDD.scala:188)
    at SimpleApp.sortBy(SimpleApp.java:118)
    at SimpleApp.main(SimpleApp.java:30)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

How do I properly put this file into HDFS, so that I can use my cluster to start working on the dataset? I also tried just adding the local file path such as:

JavaRDD<String> rdd = sc.textFile("/home/ec2-user/data.txt",8);

When I do this, and submit a job as:

./spark/bin/spark-submit --class SimpleApp --master spark://ec2-xxx.amazonaws.com:7077 --total-executor-cores 8 /home/ec2-user/simple-project-1.0.jar

I only have one executor and the worker nodes in the cluster don't seem to be getting involved. I assumed that it was because I was using a local file, and ec2 does not have a NFS.

Answer 1

因此，您需要在hdfs://data.txt //之后提供的第一部分是主机名，因此它将是hdfs://{active_master}:9000/data.txt （以防在将来，永久hdfs的带有spark-ec2脚本的默认端口为9010 ）。

Answer 2

AWS Elastic Map Reduce now supports Spark natively, and includes HDFS out of the box.

See http://aws.amazon.com/elasticmapreduce/details/spark/ , with more detail and a walkthrough in the introductory blog post .

Spark in EMR uses EMRFS to directly access data in S3 without needing to copy it into HDFS first.

The walkthrough includes an example of loading data from S3.